Systems, methods, and apparatuses for peripheral arterial disease detection and mitigation thereof

ABSTRACT

Embodiments described herein are directed to non-invasive detection of peripheral arterial disease. For example, a measuring apparatus is used to measure a patient&#39;s calf circumference. The measuring apparatus has text feature(s) or indicator(s) printed thereupon that indicate the likelihood that the patient has peripheral arterial disease based on the measured calf circumference. The assessment may be further refined by using a software application that assesses the likelihood of the patient having peripheral arterial disease using at least the calf circumference measurement, along with other information/data. Based on the assessment, a healthcare practitioner may prescribe a walking program for the patient to follow. A software application may track compliance of the walking program and provide escalating reminders to the patient if the patient continues to fail to comply with the prescribed walking program.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is continuation of U.S. application Ser. No.16/802,699, entitled “SYSTEMS, METHODS, AND APPARATUSES FOR PERIPHERALARTERIAL DISEASE DETECTION AND MITIGATION THEREOF,” filed on Feb. 27,2020, now allowed, which is a divisional application of U.S. applicationSer. No. 15/443,944, entitled “SYSTEMS, METHODS, AND APPARATUSES FORPERIPHERAL ARTERIAL DISEASE DETECTION AND MITIGATION THEREOF,” filed onFeb. 27, 2017, now U.S. Pat. No. 10,716,493, both of which areincorporated by reference herein.

BACKGROUND Technical Field

The present application relates to methods, systems, and apparatuses fornon-invasive procedures for detecting and mitigating peripheral arterialdisease.

Background Art

Peripheral arterial disease is a common circulatory problem in whichnarrowed arteries reduce blood flow to a person's limbs. When peripheralarterial disease is developed, the extremities (e.g., a person's legs)do not receive enough blood flow to keep up with the demand. This causesvarious symptoms, most notably leg pain when walking. Severe peripheralarterial disease can lead to even more extreme issues, such as kidneyfailure, foot or leg amputation, a heart attack, or a stroke. Certainprocedures, such as an angiogram or a blood test, can be used to detectthe presence of peripheral arterial disease. However, such proceduresare invasive and generally disliked by patients.

BRIEF SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

Methods, systems, and apparatuses are described for non-invasiveprocedures for detecting and mitigating peripheral arterial disease,substantially as shown in and/or described herein in connection with atleast one of the figures, as set forth more completely in the claims.

Further features and advantages of the invention, as well as thestructure and operation of various embodiments, are described in detailbelow with reference to the accompanying drawings. It is noted that theinvention is not limited to the specific embodiments described herein.Such embodiments are presented herein for illustrative purposes only.Additional embodiments will be apparent to persons skilled in therelevant art(s) based on the teachings contained herein.

BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES

The accompanying drawings, which are incorporated herein and form a partof the specification, illustrate embodiments and, together with thedescription, further serve to explain the principles of the embodimentsand to enable a person skilled in the pertinent art to make and use theembodiments.

FIG. 1A shows a block diagram of a first surface of a measuringapparatus for determining a calf circumference of a patient fordiagnosing peripheral arterial disease in accordance with an embodiment.

FIG. 1B shows a block diagram of a second surface that opposes the firstsurface of the measuring apparatus depicted in FIG. 1A in accordancewith an embodiment.

FIG. 2 shows a diagram illustrating the measuring of the circumferenceof a patient's calf using a measuring apparatus in accordance with anembodiment.

FIG. 3 shows a block diagram of a measuring apparatus having a firstsurface that is color-coded in accordance with an embodiment.

FIG. 4 shows a block diagram of a measuring apparatus having a firstsurface that is color-coded using gradients in accordance with anembodiment.

FIG. 5 shows a block diagram of a computing device configured to assesswhether a patient has peripheral arterial disease based on various typesof data in accordance with an embodiment.

FIG. 6 shows a block diagram of a system for tracking compliance of aprescribed walking program in accordance with an embodiment.

FIG. 7 depicts a flowchart of a method for tracking compliance of aprescribed walking program in accordance with an embodiment.

FIG. 8 shows a block diagram of a computing device that includes acompliance application in accordance with an embodiment.

FIG. 9 depicts a flowchart of a method for transmitting messages ofincreasing severity as a patient continues to not comply with aprescribed walking program in accordance with an embodiment.

FIG. 10 is a block diagram of a computer system in accordance with anembodiment.

The features and advantages of the embodiments described herein willbecome more apparent from the detailed description set forth below whentaken in conjunction with the drawings, in which like referencecharacters identify corresponding elements throughout. In the drawings,like reference numbers generally indicate identical, functionallysimilar, and/or structurally similar elements. The drawing in which anelement first appears is indicated by the leftmost digit(s) in thecorresponding reference number.

DETAILED DESCRIPTION I. Introduction

The present specification discloses numerous example embodiments. Thescope of the present patent application is not limited to the disclosedembodiments, but also encompasses combinations of the disclosedembodiments, as well as modifications to the disclosed embodiments.

References in the specification to “one embodiment,” “an embodiment,”“an example embodiment,” etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to affect such feature, structure, or characteristicin connection with other embodiments whether or not explicitlydescribed.

Furthermore, it should be understood that spatial descriptions (e.g.,“above,” “below,” “up,” “left,” “right,” “down,” “top,” “bottom,”“vertical,” “horizontal,” “front,” “rear,” etc.) used herein are forpurposes of illustration only, and that practical implementations of thestructures described herein can be spatially arranged in any orientationor manner.

Numerous exemplary embodiments are described as follows. It is notedthat the section/subsection headings used herein are not intended to belimiting. Embodiments described in this document may be eligible forinclusion within multiple different sections or subsections.Furthermore, disclosed embodiments may be combined with each other inany manner.

Embodiments described herein are directed to non-invasive detection ofperipheral arterial disease. For example, a measuring apparatus may beused to measure the calf circumference a patient. The measuringapparatus may have one or more text features or indicators printedthereupon that indicate the likelihood that the patient has peripheralarterial disease based on the measured calf circumference. Theassessment may be further refined by using an application that assessesthe likelihood of the patient having peripheral arterial disease usingat least the calf circumference measurement, along with otherinformation/data, such as a toe brachial index measurement associatedwith the patient, results of a walking test performed by the patient,and/or symptom-related information obtained from a questionnaire filledout by the patient. Based on the assessment, a healthcare practitioner(e.g., a doctor, a nurse, a physician's assistant, etc.) may prescribe awalking program for the patient to follow. An application may trackcompliance of the walking program and provide escalating reminders tothe patient if the patient continues to fail to comply with theprescribed walking program.

In particular, a measuring apparatus for determining a calfcircumference of a patient for diagnosing peripheral arterial disease isdescribed herein. The measuring apparatus comprises a strip of material.The strip of material comprises a first surface and a second surfacethat opposes the first surface. At least one of the first surface or thesecond surface comprises a plurality of color-coded segments arranged inseries. A first segment of the plurality of color-coded segments has afirst color and corresponds to a first range of calf circumference thatrepresents a high likelihood that the patient has peripheral arterialdisease. A second segment of the plurality of color-coded segments has asecond color that is different than the first color and corresponds to asecond range of calf circumference that represents a low likelihood thatthe patient has peripheral arterial disease.

A method performed by a computer associated with a healthcarepractitioner to determine compliance of a walking program prescribed bythe healthcare practitioner is also described herein. In accordance withthe method, first sensor data is received from a mobile device via anetwork that indicates a first number of steps a patient has takenwithin a predetermined time period. A determination is made that thefirst number of steps the patient has taken within the predeterminedtime period is not in compliance with the walking program prescribed bythe healthcare practitioner. A first message having a first severity istransmitted via the network to a device associated with the patientindicating that the patient did not comply with the prescribed walkingprogram.

A system is also described herein. The system includes at least oneprocessor circuit and at least one memory that stores program codeconfigured to be executed by the at least one process circuit. Theprogram code includes a receiver configured to receive, via a network,first sensor data from a mobile device that indicates a first number ofsteps a patient has taken within a predetermined time period. Theprogram code also includes a compliance determiner configured todetermine that the first number of steps the patient has taken withinthe predetermined time period is not in compliance with a walkingprogram prescribed by a healthcare practitioner. The program codefurther includes a transmitter configured to transmit, via the network,a first message having a first severity to a device associated with thepatient indicating that the patient did not comply with the prescribedwalking program.

These and further embodiments and variations are described in the nextsection.

II. Example Embodiments A. Measuring Apparatus Evaluation Assessment

FIGS. 1A and 1B are block diagrams of a measuring apparatus 100 fordetermining a calf circumference of a patient for diagnosing peripheralarterial disease in accordance with an embodiment. As shown in FIGS. 1Aand 1B, measuring apparatus 100 comprises a first surface 102 and asecond surface 104 that opposes first surface 102. First surface 102 mayalso be referred to as a front or outer surface of measuring apparatus100, and second surface 104 may also be referred to as a back or innersurface of measuring apparatus 100. Measuring apparatus 100 may be astrip of material having a starting point 106 (a first edge) and anending point 108 (a second edge opposed to the first edge). As shown inFIGS. 1A and 1B, the strip may be a substantially rectangular shape,although embodiments described herein are not so limited. The materialof which measuring apparatus 100 is made may comprise paper, plastic,cloth, fiber glass, metal, metal alloy, and/or any combination thereof.

First surface 102 may comprise a plurality of segments 110, 112, 114,and 116 that are arranged in series between starting point 106 andending point 108. Each of segments 110, 112, 114, and 116 may be definedvia starting point 106, ending point 108 and one or more segment markers118, 120, and 122 printed thereupon between them. For example, firstsegment 110 may be defined by the portion of first surface 102 betweenending point 108 and segment marker 118. Second segment 112 may bedefined by the portion of first surface 102 between segment marker 118and segment marker 120. Third segment 114 may be defined by the portionof first surface 102 between segment marker 120 and segment marker 122.Fourth segment 116 may be defined by the portion of first surface 102between segment marker 122 and starting point 106.

Each segment of measuring apparatus 100 may correspond to a calfthickness and corresponding likelihood that a patient has peripheralarterial disease. For instance, in an embodiment, first segment 110corresponds to a first range of calf thickness that represents a lowlikelihood that the patient has peripheral arterial disease. Secondsegment 112 corresponds to a second range of calf thickness thatrepresents a medium likelihood that the patient has peripheral arterialdisease. Third segment 114 corresponds to a third range of calfthickness that represents a high likelihood that the patient hasperipheral arterial disease. Fourth segment 116 may be a portion ofmeasuring apparatus 110 that a user holds while wrapping measuringapparatus 100 around the calf of the patient and may not be used as anindicator of the likelihood that the patient has peripheral arterialdisease. It is further noted that while measuring apparatus 100 isdepicted as having four segments (i.e., segments 110, 112, 114, and116), measuring apparatus 100, in other embodiments, other numbers ofsegments may be present that correspond to calf thicknesses and diseaselikelihoods.

As shown in FIG. 1A, one or more segments may include markings printedthereupon that are indicative of the likelihood that the patient hasperipheral arterial disease. For example, first segment 110 may includea text feature 124 (“Low Likelihood”), second segment 112 may include atext feature 126 (“Medium Likelihood”), and third segment 114 mayinclude a text feature 128 (“High Likelihood”). It is noted that textfeatures 124, 126, and 128 are merely exemplary and that any text and/orgraphical feature may be used to represent various likelihoods of apatient having peripheral arterial disease. Fourth segment 116 may notinclude any markings printed thereupon (i.e., segment 116 may be blank)or may indicate fourth segment 116 as intended for a user's hand, etc.

Measuring apparatus 100 and each segment thereof may have acorresponding length. For instance, in accordance with an embodiment,the length of measuring apparatus is approximately 60 cm (e.g.,measuring apparatus 100 may have a length between 59 and 61 cm). Inaccordance with such an embodiment, first segment 110 is approximately17 centimeters in length (e.g., first segment 110 may have a lengthbetween 16-18 centimeters), second segment 112 is approximately 9centimeters in length (e.g., second segment 112 may have a lengthbetween 8-10 centimeters), third segment 114 is 20 centimeters in length(e.g., third segment 110 may have a length between 19-21 centimeters),and fourth segment 116 is approximately 14 centimeters in length (e.g.fourth segment 116 may have a length between 13-15 centimeters).

In an embodiment, the length of each of segments 110, 112, and 114 maybe based on statistical analysis of data associated with a plurality ofpatients (e.g., thousands of patients). The data may be maintained in apublic database (e.g., a National Health and Nutrition ExaminationSurvey (NHANES) database) that includes information regarding patientswith and without peripheral arterial disease. After applying ageneralized linear statistical model and/or a random forest machinelearning model to the data, and after controlling for traditional riskfactors (e.g., age, ethnicity, smoking, hypertension, body mass index(BMI)), it has been observed that calf circumference is a strongindependent predictor of the present of peripheral arterial disease. Inparticular, it has been observed that a calf circumference less than 34cm is an indicator that a patient has a high likelihood of havingperipheral arterial disease, a calf circumference greater than 43 cm isan indicator that a patient has a low likelihood of having peripheralarterial disease, and a calf circumference having a range therebetween(e.g., between 34 cm and 43 cm) is an indicator that a patient has amedium likelihood of having peripheral arterial disease.

As also shown in FIG. 1B, second surface 104 may be blank (i.e., secondsurface 104 may have not markings printed thereupon). Alternatively,second surface 104 may have the same markings as first surface 102. Thatis, second surface 104 may be identical to first surface 102.

The likelihood that the patient has peripheral arterial disease may bedetermined by measuring the circumference of the calf of the patientusing measuring apparatus 100. For example, FIG. 2 shows a diagram 200illustrating the measuring the circumference of a patient's calf usingmeasuring apparatus 100 in accordance with an embodiment. As shown inFIG. 2 , measuring apparatus 100 is wrapped around calf 202 such thatfirst surface 102 faces away from calf 202 and a loop is formed aroundcalf 202. Measuring apparatus 100 may be moved up and down calf 202 inorder to find the portion of calf 202 having the largest circumference.The likelihood that the patient has peripheral arterial disease can beobtained by reading the markings on first surface 202 at the point wherestarting point 106 of measuring apparatus 100 intersects second surface104. For example, if the point where starting point 106 intersectssecond surface 104 is within first segment 110, it may be determinedthat the patient has a low likelihood of peripheral arterial disease. Ifthe point where starting point 106 intersects second surface 104 iswithin second segment 112, it may be determined that the patient has amedium likelihood of peripheral arterial disease. If the point wherestarting point 106 intersects second surface 104 is within third segment114, it may be determined that the patient has a high likelihood ofperipheral arterial disease. In the example shown in FIG. 2 , measuringapparatus 100 indicates that the patient has medium likelihood of havingperipheral arterial disease.

In accordance with an embodiment, segments 110, 112, 114, and 116 may bedefined by different colors (in addition to or in lieu of using segmentmarkers 118, 120, and 122), thereby forming a color-coded measuringapparatus. For example, FIG. 3 is a block diagram of measuring apparatus100 in which first surface 102 is color-coded in accordance with anembodiment. As shown in FIG. 3 , first segment 110 is defined by theportion of first surface 102 that has a first color (e.g., green),second segment 112 is defined by the portion of first surface 102 thathas a second color (e.g., yellow or orange), third segment 114 isdefined by the portion of first surface 102 that has a third color(e.g., red), and fourth segment 116 is defined by the portion of firstsurface 102 that has a fourth color (e.g., white). It is noted that thecolors described above are merely exemplary and that each of segments110, 112, 114, and 116 may be any color, including a range of grayshades (i.e., grayscale) or other shades of a single or multiple colors.

In accordance with an embodiment, the color of each segments 110, 112,114, and 116 may be represented as a gradient. For example, FIG. 4 is ablock diagram of measuring apparatus 100 in which first surface 102 iscolor-coded using gradients in accordance with an embodiment. Forinstance, first segment 110 may be defined by the portion of firstsurface 102 having a first gradient being based on first color (e.g.,green), second segment 112 may be defined by the portion of firstsurface 102 having a second gradient being based on second color (e.g.,yellow or orange), and third segment 114 may be defined by the portionof first surface 102 having a third gradient being based on a thirdcolor (e.g., red). Fourth segment 116 may be defined by the portion offirst surface 102 having no gradient and may simply be a solid color(e.g., white). It is noted that the gradients described above are merelyexemplary and that each of segments 110, 112, 114, and 116 may havegradients based on any color, including a range of gray shades (i.e.,grayscale).

Measuring apparatus 100 may further include one or more additionalfeatures printed thereupon. For example, as further shown in FIG. 4 ,first surface 102 may include a set of length markings 402 that dividefirst surface 102 by standard units of length (e.g., centimeters). It isnoted that while FIG. 4 depicts the standard unit of length to becentimeters, any standard of unit of length may be used (e.g., inches,millimeters, etc.). As also shown in FIG. 4 , first surface 102 may alsoinclude a first indicator 404, a second indicator 406, a third indicator408, a fourth indicator 410, and/or a fifth indicator 412 printedthereupon. First indicator 404 may represent the mean of patients thatdo not have peripheral arterial disease. Second indicator 406 mayrepresent the standard error of mean of patients without peripheralarterial disease. Third indicator 408 may represent the mean of patientsthat have peripheral arterial disease. Fourth indicator 410 mayrepresent the mean plus the standard deviation of the patients that haveperipheral arterial disease. Fifth indicator 412 may represent the meanminus the standard deviation of the patients that have peripheralarterial disease. The above-described means, standard error of means andstandard deviations may be based on the statistical analysis performedon data associated with a plurality of patients as described above.

In an embodiment, second surface 104 (as shown in FIG. 1B) may includethe same color scheme as shown in FIGS. 3 and 4 and/or each of markings402, 404, 406, 408, 410 and/or 412 shown in FIG. 4 , may includeinstructions for using measuring apparatus 100, and/or may be markedand/or colored/shaded in other ways.

B. Screening Application

As described above in Subsection ILA, a measuring apparatus may be usedto assess the likelihood as to whether a patient has peripheral arterialdisease. The assessment may be further refined using additional dataregarding the patient. For example, the data may be analyzed by anapplication to make a refined assessment as to whether the patient hasperipheral arterial disease.

FIG. 5 is a block diagram of a computing device 500 configured to assesswhether a patient has peripheral arterial disease based on various typesof data in accordance with an example embodiment. Computing device 500may be any type of stationary or mobile computing device, including adesktop computer (e.g., a personal computer, etc.), a mobile computer orcomputing device (e.g., a Palm® device, a RIM Blackberry® device, apersonal digital assistant (PDA), a laptop computer, a notebookcomputer, a tablet computer (e.g., an Apple iPad™), a smart phone (e.g.,an Apple iPhone, a Google Android™ phone, a Microsoft Windows® phone,etc.), or other type of computing device. As shown in FIG. 5 , computingdevice 500 includes a screener application 502.

Screener application 502 may be a software application that executes inhardware, and is configured to receive data associated with a patientand make an assessment as to whether the patient has peripheral arterialdisease based on the data. The data includes one or more of measuringapparatus data 506, exercise data 508, diagnostic test data 510 and/orquestionnaire data 512. Screener application 502 may include a userinterface 504 that enables a user to enter in measuring apparatus data506, exercise data 508, diagnostic test data 510 and/or questionnairedata 512.

Measurement apparatus data 506 may comprise one or more measurementstaken using the measuring apparatus described above in Subsection A. Forexample, the measurement(s) may include the determined likelihood thatthe patient has peripheral arterial disease (e.g., a low likelihood, amedium likelihood, or a high likelihood) and/or the calf circumference(e.g., in centimeters). The determined likelihood and/or calfcircumference is provided to screener application 502 via user interface504.

Exercise data 508 may comprise data associated with one or moreexercises that the patient has performed. For example, it has beenobserved that peripheral arterial disease limits the walking ability ofpatients. A six-minute walk test has been shown to be a reliable and areproducible method of assessing this limitation. The six-minute walktest assesses the distance that a patient walks at a normal pace duringsix minutes. Exercise data 508 may include results of a patient'ssix-minute walk test (i.e., the distance traveled (e.g., the number offeet, meters, etc.) in six minutes). The distance traveled may beindicative of whether the patient has peripheral arterial disease. Forexample, if the patient is able to walk less than a predeterminedthreshold (e.g., 300 meters) within six minutes, this may be anindication, or a determination, that the patient may have peripheralarterial disease. It is noted that the predetermined threshold isexemplary, and other thresholds may be used. It is further noted thatthe threshold may vary depending on certain characteristics of thepatient (e.g., age, weight, etc.). The distance traveled is provided toscreener application 502 via user interface 504.

Diagnostic test data 510 may comprise data associated with one or morediagnostic tests performed on the patient. One such exam is a toebrachial index exam. It has been observed that patients with peripheralarterial disease have blockages in the arteries to the extremities.Thus, pressure in the involved extremity would be lower than that in theuninvolved extremity. Calcification of the patient's medium-sizedarteries makes pressure measurement unreliable in the involved bloodvessels. Toe pressure measurement avoids this error. Thus, a ratio ofthe toe pressure to the arm pressure (also referred to as the toebrachial index (TBI)) provides a measure of the presence (or absence) ofperipheral arterial disease. The toe and/or arm pressure may bedetermined using known techniques, such, but not limited to, acontinuous wave Doppler, a sphygmomanometer, and/or pressure cuffs. TheTBI may be determine before and/or after the six-minute walk test. A TBIthat is lower than 0.7 or higher than 1.3 may indicate the presence ofperipheral arterial disease. Additionally, an absolute toe pressure lessthan 50 millimeters of mercury (mmHg) may indicate critical limbischemia (if a leg wound forms, it may not heal). The determined TBI(s)are provided to screener application 502 via user interface 504.

Questionnaire data 512 may comprise data collected via one or morequestions provided to the patient that are directed to determining theseverity of various patient symptoms. Such questions may inquire aboutthe severity of pain and/or the numbness in the patient's leg and/orfoot while walking, the severity of weakness or tiredness in thepatient's leg and/or foot, the severity of pain in the patient's legand/or foot while resting, whether the patient has had any pain in theleg and/or foot while resting, etc. The level of severity for each ofthe symptoms indicated by the patient may be indicative of peripheralarterial disease (where the more severe the symptoms, the more likelythe patient has peripheral arterial disease). The answers to thequestions are provided to screener application 502 via user interface504.

Screener application 502 may be configured to use the above-describedmeasuring apparatus data 506, exercise data 508, diagnostic test data510 and/or questionnaire data 512 to provide a comprehensive report ofthe patient and make an assessment as to whether the patient hasperipheral arterial disease and the severity thereof. The severity ofperipheral arterial disease may be based on a combination of the datathat indicates whether the patient likely has peripheral arterialdisease. For example, if each of measuring apparatus data 506, exercisedata 508, diagnostic test data 510 and/or questionnaire data 512 areindicative of the patient having peripheral arterial disease, thenscreener application 502 may determine that patient has the most severecase of peripheral arterial disease. Conversely, if none of measuringapparatus data 506, exercise data 508, diagnostic test data 510 and/orquestionnaire data 512 are indicative of the patient having peripheralarterial disease, screener application 502 may determine that thepatient does not have peripheral arterial disease. A weighting of thevarious data may be combined to generate an overall assessment, whichmay be compared to one or more threshold levels to indicate the patientdoes have or does not have peripheral arterial disease, or provide somelikelihood in between (e.g., medium likelihood). Severity of peripheralarterial disease may be adjudicated using non-invasive physiologicalmeasurements, which are important predictor of outcome than anatomicalangiographic measurements. Machine learning techniques may be used andrefined to further categorize likelihood and severity of peripheralarterial disease.

C. Prescribed Walking Program Compliance

After a determination is made that a patient likely has peripheralarterial disease, a healthcare practitioner may prescribe a walkingprogram for the patient to follow. The goal of the walking program is tomitigate the effects of peripheral arterial disease. The patient maycarry a computing device that executes a software application thattracks the distance the patient has travelled. The distance travelledmay be transmitted to a computing device associated with the healthcarepractitioner. The healthcare practitioner's computing device may assesswhether the patient has complied with the prescribed walking programbased on the received distance travelled. If it is determined that thepatient has not complied with the prescribed walking program, thecomputing device may transmit escalating reminders to the patient thatincrease in severity. For example, the first time the patient does notcomply with the prescribed walking program, the patient may receive amessage via the application that tracks the distance travelled by theuser reminding the patient to comply with the prescribed walking program(e.g., “Don't forget to walk 1000 steps today”). The second time thepatient does not comply with the prescribed walking program, the patientmay receive a more urgent message (e.g., text message) reminding thepatient to comply with the prescribed walking program (“e.g., “URGENT:REFUSAL TO COMPLY WITH YOUR PRESCRIBED WALKING PROGRAM MAY WORSEN YOURSYMPTOMS!!!”). Thereafter, the patient may receive a phone call from thehealthcare practitioner to remind the patient to comply with theprescribed walking program, and ultimately, would receive a phone callfrom the healthcare practitioner to schedule an appointment therewith.

FIG. 6 is a block diagram of a system for tracking compliance of aprescribed walking program in accordance with an embodiment. As shown inFIG. 6 , system 600 includes a mobile device 602 and a computing device604. Mobile device 602 and computing device 604 may each may compriseany of a wide variety of portable electronic devices mentioned herein orotherwise known, including but not limited to a smart phone, a tabletcomputer, a laptop computer, a wearable computing device, a wearablefitness device, a pedometer, a personal media player, or the like.Mobile device 602 and computing device 604 are each presented herein byway of example only.

As shown in FIG. 6 , mobile device 602 includes a processing unit 606.Processing unit 604 comprises a central processing unit (CPU), amicroprocessor, a multi-core processor, or other integrated circuit thatis configured to execute computer program instructions that areretrieved from memory (e.g., memory 614), thereby causing certainoperations to be performed. As further shown in FIG. 6 , processing unit606 is connected to one or more user input components 608, one or moreuser output component 610, one or more sensors 612, and a memory 614.

User input component(s) 608 may comprise one or more of a touch screen,keypad, button, microphone, camera, or other component suitable forenabling a user to provide input to mobile device 602. User outputcomponent(s) 610 may comprise one or more of a display, audio speaker,haptic feedback element, or other component suitable for providingoutput to a user of mobile device 602.

Sensor(s) 612 may comprise an accelerometer and/or a gyroscope. Theaccelerometer may be configured to measure acceleration forces. In anembodiment, the accelerometer comprises a 3-axis accelerometer that isconfigured to measure acceleration along each of three orthogonal axesof a right-handed mobile device reference frame. The three axes may bedenoted the x-axis, the y-axis, and the z-axis. In an embodiment inwhich mobile device 602 comprises a mobile phone having a generallyrectangular display on one side thereof, the x-axis may run along theshort side of the display, the y-axis may run along the long side of thedisplay, and the z-axis may run perpendicular to and out of the front ofthe display. However, other mobile device reference frames may be used.Each acceleration measurement may be represented in meters per secondsquared (m/s²) or other suitable unit of measurement. The gyroscope maybe configured to measure orientation of mobile device 602. In anembodiment, the gyroscope comprises a 3-axis MEMS gyroscope that isconfigured to measure a rate of rotation around each of the axes of theaforementioned mobile device reference frame. Each gyroscope measurementmay be represented in radians per second (rad/s) or other suitable unitof measurement.

Memory 614 comprises one or more volatile or non-volatile memory devicesthat are operable to store computer program instructions (also referredto herein as computer program logic). These computer programinstructions may be retrieved from memory 614 and executed by processingunit 606 in a well-known manner to cause processing unit 606 to performcertain operations.

As further shown in FIG. 6 , memory 614 stores tracker application 616.Tracker application 616 comprises computer program instructions that,when executed by processing unit 606, causes processing unit 606 toperform an algorithm for determining a number of steps taken or adistance travelled by a patient within a predetermined time period usingdata collected from sensor(s) 612. Based on the teachings providedherein, persons skilled in the relevant art(s) will appreciate that themethod for determining a distance travelled by a patient predeterminedtime period can be implemented by other devices and systems as well.

Sensor data indicative of the number of steps and/or distance travelledmay be provided to computing device 604 via network 618. Network 618 maybe a LAN (local area network), a WAN (wide area network), or anycombination of networks, such as the Internet. Computing device 604 iscoupled to network 618 through a communication link 620, and mobiledevice 602 is coupled with network 618 through a communication link 622.Communication links 620 and 622 may each include wired and/or wirelesslinks. Examples of communication links 620 and 622 include IEEE 802.11wireless LAN (WLAN) wireless links, Worldwide Interoperability forMicrowave Access (Wi-MAX) links, cellular network links, wirelesspersonal area network (PAN) links (e.g., Bluetooth™ links), Ethernetlinks, USB (universal serial bus) links, etc.

Computing device 604 may be a device associated with a healthcarepractitioner. For example, computing device 604 may be located at theoffice, hospital, etc. of the healthcare practitioner. As shown in FIG.6 , computing device 604 may include a processing unit 624, inputcomponent(s) 626, user output component(s) 628, and a memory 630.Processing unit 624, user input component(s) 626, user outputcomponent(s) 628, and memory 630 are examples of processing unit 606,user input component(s) 608, user output component(s) 610, and memory614, and therefore, may operate in a similar manner as described above.As shown in FIG. 6 , memory 630 stores a compliance application 632.Compliance application 632 comprises computer program instructions that,when executed by processing unit 624, causes processing unit 624 toperform an algorithm for determining whether a patient has complied witha walking program prescribed by the healthcare practitioner based on thesensor data provided by tracker application 616.

For example, compliance application 632 may provide a user interfacethat enables a healthcare practitioner to enter in a walking program(e.g., using user input component(s) 626) that a patient is to complywith. Examples of a walking program may include, but are not limited to,walking 1000 meters in a day, 5000 meters in a week, etc. Complianceprogram 632 may compare the number of steps and/or distance travelledwithin the predetermined time period indicated by the sensor datareceived from mobile device 602 to the walking program and determinewhether the patient has complied with the walking program. If complianceprogram 632 determines that the patient has not complied with theprescribed walking program, compliance program may transmit escalatingreminders to the patient that increase in severity if the patientcontinues to not comply with the prescribed walking program. Forexample, the first time the patient does not comply with the prescribedwalking program, compliance program 632 may transmit a command totracker application 616 (e.g., via network 618) that causes trackerapplication 616 to display a message reminding the patient to complywith the walking program. The second time the patient does not complywith the prescribed walking program, compliance program 632 may cause atext message (e.g., a short messaging system (SMS) message) to betransmitted to mobile device 602 and/or other another computing deviceassociated with the patient (e.g., the patient's smart phone, tablet,etc.). Alternatively, compliance program 632 may display a notificationvia computing device 604 (e.g., using user output component(s) 628) thatindicates that the healthcare practitioner should transmit a textmessage (e.g., by using the healthcare practitioner's phone) to mobiledevice 602 and/or another computing device associated with the patient.The third time the patient does not comply with the prescribed walkingprogram, compliance program 632 may display a notification via computingdevice 604 that indicates that the healthcare practitioner should callthe patient to remind the patient to comply with the prescribed walkingprogram. The fourth time the patient does not comply with the prescribedwalking program, compliance program 632 may display a notification viacomputing device 604 that indicates that the healthcare practitionershould call the patient to schedule an appointment for the patient tovisit the healthcare practitioner. It is noted that the remindersdescribed do not necessarily have to be transmitted to the patient eachtime the patient fails to comply with the prescribed walking program.Instead, a reminder may be transmitted every Nth time a patient fails tocomply with the prescribed walking program, where N is any integergreater than one. Furthermore, different numbers and types of remindersmay be used in other embodiments.

Accordingly, in embodiments, compliance of a prescribed walking programmay be tracked in many ways. For instance, FIG. 7 shows a flowchart 700of a method for tracking compliance of a prescribed walking program inaccordance with an embodiment. The method of flowchart 700 may beimplemented by a computing device 804 shown in FIG. 8 . FIG. 8 depicts ablock diagram 800 of computing device 804 in accordance with anembodiment. Computing device 804 is an example of computing device 604described above with reference to FIG. 6 . As shown in FIG. 8 ,computing device 804 includes a compliance application 832. Complianceapplication 832 is an example of compliance application 632 describedabove with reference to FIG. 6 . Compliance application 832 includescompliance determiner 802, a receiver 806, and a transmitter 808. Otherstructural and operational embodiments will be apparent to personsskilled in the relevant art(s) based on the following discussionregarding flowchart 700 and computing device 804.

Flowchart 700 begins with step 702. At step 702, first sensor data isreceived via a network from a mobile device that indicates a firstnumber of steps a patient has taken within a predetermined time period.For example, with reference to FIG. 8 , receiver 806 may receive firstsensor data 801 via a network (e.g., network 618, as shown in FIG. 6 )from a mobile device (e.g., mobile device 602, as shown in FIG. 6 ).First sensor data 801 may indicate a first number of steps a patient hastaken within a predetermined time period. First sensor data 801 isprovided to compliance determiner 802.

At step 704, a determination is made that the first number of steps thepatient has taken within the predetermined time period is not incompliance with the walking program prescribed by the healthcarepractitioner. For example, with reference to FIG. 8 , compliancedeterminer 802 determines that the first number of steps the patient hastaken within the predetermined time period is not in compliance with thewalking program prescribed by the healthcare practitioner.

At step 706, a first message having a first severity is transmitted viathe network to a device associated with the patient indicating that thepatient did not comply with the prescribed walking program. For example,with reference to FIG. 8 , compliance determiner 802 generates a firstmessage 803 having a first severity that indicates that the patient didnot comply with the prescribed walking program. First message 803 isprovided to transmitter 808. Transmitter 808 transmits first message 803to a device associated with the patient via the network (e.g., network618).

In accordance with one or more embodiments, the device associated withthe patient is the mobile device (e.g., mobile device 602, as shown inFIG. 6 ).

In accordance with one or more embodiments, the device associated withthe patient is a computing device associated with the user other thanthe mobile device (e.g., the patient's smart phone, tablet, etc.).

In accordance with one or more embodiments, the first message isconfigured to be displayed via an application executing on the deviceassociated with the patient. For example, with reference to FIG. 6 , thefirst message is configured to be displayed via tracker application 616executing on mobile device 602. For instance, tracker application 616may cause user output component(s) 610 to display the first message.

In accordance with one or more embodiments, the prescribed walkingprogram is based on a distance that the patient is able to walk withinthe predetermined time period.

In accordance with an embodiment, computing device 804 uses a singletransceiver rather than a separate transmitter and receiver (i.e.,receiver 806 and transmitter 808) for performing communication via thenetwork.

In some example embodiments, one or more of steps 702, 704, and/or 706of flowchart 700 may not be performed. Moreover, operations in additionto or in lieu of steps 702, 704, and/or 706 may be performed. Further,in some example embodiments, one or more of steps 702, 704, and/or 706may be performed out of order, in an alternate sequence, or partially(or completely) concurrently with each other or with other operations.

In accordance with one or more embodiments, compliance application 832is configured to transmit messages of increasing severity as the patientcontinues to not comply with the prescribed walking program. Forinstance, FIG. 9 shows a flowchart 900 of a method for transmittingmessages of increasing severity as the patient continues to not complywith a prescribed walking program in accordance with an embodiment. Themethod of flowchart 900 may be implemented by a computing device 804shown in FIG. 8 . Accordingly, FIG. 9 will be described with continuedreference to FIG. 8 . Other structural and operational embodiments willbe apparent to persons skilled in the relevant art(s) based on thefollowing discussion regarding flowchart 900 and computing device 804.

Flowchart 900 begins with step 902. At step 902, second sensor data isreceived via the network from the mobile device that indicates a secondnumber of steps a patient has taken within the predetermined timeperiod. For example, with reference to FIG. 8 , receiver 806 may receivesecond sensor data 805 via a network (e.g., network 618, as shown inFIG. 6 ) from a mobile device (e.g., mobile device 602, as shown in FIG.6 ). Second sensor data 805 may indicate a second number of steps apatient has taken within the predetermined time period. First sensordata 805 is provided to compliance determiner 802.

At step 804, a determination is made that the second number of steps thepatient has taken within the predetermined time period is not incompliance with the walking program prescribed by the healthcarepractitioner. For example, with reference to FIG. 8 , compliancedeterminer 802 determines that the second number of steps the patienthas taken within the predetermined time period is not in compliance withthe walking program prescribed by the healthcare practitioner.

At step 806, a second message having a second severity that is greaterthan the first severity is transmitted via the network to the deviceassociated with the patient indicating that the patient did not complywith the prescribed walking program. For example, with reference to FIG.8 , compliance determiner 802 generates a second message 807 having asecond severity that is greater than the first severity indicates thatthe patient did not comply with the prescribed walking program. Secondmessage 807 is provided to transmitter 808. Transmitter 808 transmitssecond message 807 to a device associated with the patient via thenetwork (e.g., network 618).

In accordance with one or more embodiments, the second message is a textmessage.

In some example embodiments, one or more of steps 902, 904, and/or 906of flowchart 900 may not be performed. Moreover, operations in additionto or in lieu of steps 902, 904, and/or 906 may be performed. Further,in some example embodiments, one or more of steps 902, 904, and/or 906may be performed out of order, in an alternate sequence, or partially(or completely) concurrently with each other or with other operations.

D. Additional Embodiments

1. Tissue Loss Determination

Peripheral arterial disease is known to cause tissue loss. It has beenobserved that such tissue loss can result in the loss of calfcircumference. The measuring apparatus described above in Subsection Amay be also be used to quantify tissue loss. For example, the measuringapparatus may be used to periodically measure the calf circumference. Ifthe measurements indicate that the measured calf circumference decreasesover time, then it may be determined that the patient has suffered fromtissue loss.

2. Fall Risk Assessment

A leading cause of death in the United States among the elderly isfalling. One contributed factor may be a smaller calf circumference,along with other factors, such as visual acuity, age of shoes andcertain environment issues (e.g., loose rugs, a lack of handicap handlesat the home, etc.). In accordance with an embodiment, screenerapplication 502, as described above with reference to FIG. 5 , may beconfigured to determine the risk of the patient falling based on themeasured calf circumference and the additional factors described above.For example, the patient may be required to fill out a questionnaireasking the patient to identify the above-described factors. Thepatient's answers may be provided to screener application 502 asquestionnaire data 512, along with measuring apparatus data 506 (i.e.,measured calf circumference). Screener application 502 may be configuredto assess the risk of the patient falling based on questionnaire data512 and/or measuring apparatus data 506 and provide a score of the riskof the patient falling accordingly.

III. Further Example Embodiments

A device, as defined herein, is a machine or manufacture as defined by35 U.S.C. § 101. That is, as used herein, the term “device” refers to amachine or other tangible, manufactured object and excludes software andsignals. Devices may include digital circuits, analog circuits, or acombination thereof. Devices may include integrated circuits (ICs), oneor more processors (e.g., central processing units (CPUs),microprocessors, digital signal processors (DSPs), etc.) and/or may beimplemented with any semiconductor technology, including one or more ofa Bipolar Junction Transistor (BJT), a heterojunction bipolar transistor(HBT), a metal oxide field effect transistor (MOSFET) device, a metalsemiconductor field effect transistor (MESFET) or other transconductoror transistor technology device. Such devices may use the same oralternative configurations other than the configuration illustrated inembodiments presented herein.

Techniques and embodiments, including methods, described herein may beimplemented in hardware (digital and/or analog) or a combination ofhardware and software and/or firmware. Techniques described herein maybe implemented in one or more components. Embodiments may comprisecomputer program products comprising logic (e.g., in the form of programcode or instructions as well as firmware) stored on any computer useablestorage medium, which may be integrated in or separate from othercomponents. Such program code, when executed in one or more processors,causes a device to operate as described herein. Devices in whichembodiments may be implemented may include storage, such as storagedrives, memory devices, and further types of computer-readable media.Examples of such computer-readable storage media include, but are notlimited to, a hard disk, a removable magnetic disk, a removable opticaldisk, flash memory cards, digital video disks, random access memories(RAMs), read only memories (ROM), and the like. In greater detail,examples of such computer-readable storage media include, but are notlimited to, a hard disk associated with a hard disk drive, a removablemagnetic disk, a removable optical disk (e.g., CDROMs, DVDs, etc.), zipdisks, tapes, magnetic storage devices, MEMS (micro-electromechanicalsystems) storage, nanotechnology-based storage devices, as well as othermedia such as flash memory cards, digital video discs, RAM devices, ROMdevices, and the like. Such computer-readable storage media may, forexample, store computer program logic, e.g., program modules, comprisingcomputer executable instructions that, when executed, provide and/ormaintain one or more aspects of functionality described herein withreference to the figures, as well as any and all components, steps andfunctions therein and/or further embodiments described herein.

Computer readable storage media are distinguished from andnon-overlapping with communication media. Communication media embodiescomputer-readable instructions, data structures, program modules orother data in a modulated data signal such as a carrier wave. The term“modulated data signal” means a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal. By way of example, and not limitation, communicationmedia includes wired media as well as wireless media such as acoustic,RF, infrared and other wireless media. Example embodiments are alsodirected to such communication media.

The peripheral arterial disease assessment, fall risk assessment and/orthe tracking of a prescribed walking program compliance embodimentsand/or any further systems, sub-systems, and/or components disclosedherein may be implemented in hardware (e.g., hardware logic/electricalcircuitry), or any combination of hardware with software (computerprogram code configured to be executed in one or more processors orprocessing devices) and/or firmware.

The embodiments described herein, including systems, methods/processes,and/or apparatuses, may be implemented using well known processingdevices, telephones (smart phones and/or mobile phones), servers,electronic devices (e.g., consumer electronic devices) and/or,computers, such as a computer 1000 shown in FIG. 10 . It should be notedthat computer 1000 may represent communication devices, processingdevices, servers, and/or traditional computers in one or moreembodiments. For example, computing device 500, screener application502, tracker application 616, compliance application 632, mobile device602, computing device 604, computing device 804, and/or complianceapplication 832 (as described above with reference to FIGS. 5, 6, and 8, respectively), and/or any of the sub-systems, components orsub-components respectively contained therein, may be implemented usingone or more computers 1000.

Computer 1000 can be any commercially available and well knowncommunication device, processing device, and/or computer capable ofperforming the functions described herein, such as devices/computersavailable from International Business Machines®, Apple®, Sun®, HP®,Dell®, Cray®, Samsung®, Nokia®, etc. Computer 1000 may be any type ofcomputer, including a desktop computer, a server, etc.

Computer 1000 includes one or more processors (also called centralprocessing units, or CPUs), such as a processor 1006. Processor 1006 isconnected to a communication infrastructure 1002, such as acommunication bus. In some embodiments, processor 1006 cansimultaneously operate multiple computing threads.

Computer 1000 also includes a primary or main memory 1008, such asrandom access memory (RAM). Main memory 1008 has stored therein controllogic 1024 (computer software), and data.

Computer 1000 also includes one or more secondary storage devices 1010.Secondary storage devices 1010 include, for example, a hard disk drive1012 and/or a removable storage device or drive 1014, as well as othertypes of storage devices, such as memory cards and memory sticks. Forinstance, computer 1000 may include an industry standard interface, sucha universal serial bus (USB) interface for interfacing with devices suchas a memory stick. Removable storage drive 1014 represents a floppy diskdrive, a magnetic tape drive, a compact disk drive, an optical storagedevice, tape backup, etc.

Removable storage drive 1014 interacts with a removable storage unit1016. Removable storage unit 1016 includes a computer useable orreadable storage medium 1018 having stored therein computer software1026 (control logic) and/or data. Removable storage unit 1016 representsa floppy disk, magnetic tape, compact disk, DVD, optical storage disk,or any other computer data storage device. Removable storage drive 1014reads from and/or writes to removable storage unit 1016 in a well-knownmanner.

Computer 1000 also includes input/output/display devices 1004, such astouchscreens, LED and LCD displays, monitors, keyboards, pointingdevices, etc.

Computer 1000 further includes a communication or network interface1018. Communication interface 1020 enables computer 1000 to communicatewith remote devices. For example, communication interface 1020 allowscomputer 1000 to communicate over communication networks or mediums 1022(representing a form of a computer useable or readable medium), such asLANs, WANs, the Internet, etc. Network interface 1020 may interface withremote sites or networks via wired or wireless connections.

Control logic 1028 may be transmitted to and from computer 1000 via thecommunication medium 1022.

Any apparatus or manufacture comprising a computer useable or readablemedium having control logic (software) stored therein is referred toherein as a computer program product or program storage device. Thisincludes, but is not limited to, computer 1000, main memory 1008,secondary storage devices 1010, and removable storage unit 1016. Suchcomputer program products, having control logic stored therein that,when executed by one or more data processing devices, cause such dataprocessing devices to operate as described herein, represent embodimentsof the invention.

Any apparatus or manufacture comprising a computer useable or readablemedium having control logic (software) stored therein is referred toherein as a computer program product or program storage device. Thisincludes, but is not limited to, a computer, computer main memory,secondary storage devices, and removable storage units. Such computerprogram products, having control logic stored therein that, whenexecuted by one or more data processing devices, cause such dataprocessing devices to operate as described herein, represent embodimentsof the inventive techniques described herein.

IV. Conclusion

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and notlimitation. It will be apparent to persons skilled in the relevantart(s) that various changes in form and detail can be made thereinwithout departing from the spirit and scope of the embodiments. Thus,the breadth and scope of the embodiments should not be limited by any ofthe above-described exemplary embodiments, but should be defined only inaccordance with the following claims and their equivalents.

What is claimed is:
 1. A measuring apparatus for determining a calfcircumference of a patient for diagnosing peripheral arterial disease,comprising: a strip of material comprising opposing first and secondsurfaces, wherein at least one of the first surface or the secondsurface comprise: a first segment corresponding to a first range of calfcircumference that represents a low likelihood that the patient hasperipheral arterial disease, a second segment corresponding to a secondrange of calf circumference that represents a medium likelihood that thepatient has peripheral arterial disease, and a third segmentcorresponding to a third range of calf circumference that represents ahigh likelihood that the patient has peripheral arterial disease,wherein the first segment, the second segment, and the third segment arearranged in series.
 2. The measuring apparatus of claim 1, wherein thefirst segment, the second segment, and the third segment are each markedwith a graphical feature corresponding to their respective likelihoodthat the patient has peripheral arterial disease.
 3. The measuringapparatus of claim 1, wherein the first segment, the second segment, andthe third segment are each marked with a textual feature correspondingto their respective likelihood that the patient has peripheral arterialdisease.
 4. The measuring apparatus of claim 1, wherein a respectivelength of each of the first segment, the second segment, and the thirdsegment is based on statistical analysis of data associated with aplurality of patients.
 5. The measuring apparatus of claim 1, whereinthe first surface further comprises a first indicator that represents amean plus standard deviation of the patients that have peripheralarterial disease.
 6. The measuring apparatus of claim 1, wherein thefirst segment and the second segment are separated by a first segmentmarker, and the second segment and the third segment are separated by athird segment marker.
 7. The measuring apparatus of claim 1, wherein theat least one of the first surface or the second surface furthercomprise: a fourth segment in series with the first segment, adjacent tothe first segment, and configured to be held by a user that wrapsmeasuring apparatus around the calf of the patient.
 8. A method fordetermining a calf circumference of a patient for diagnosing peripheralarterial disease, comprising: wrapping around the calf a measuringapparatus that comprises a strip of material comprising opposing firstand second surfaces, wherein the first surface comprises: a firstsegment corresponding to a first range of calf circumference thatrepresents a low likelihood that the patient has peripheral arterialdisease, a second segment corresponding to a second range of calfcircumference that represents a medium likelihood that the patient hasperipheral arterial disease, and a third segment corresponding to athird range of calf circumference that represents a high likelihood thatthe patient has peripheral arterial disease, wherein the first segment,the second segment, and the third segment are arranged in series; andreading a marking on the first surface where a starting point ofmeasuring apparatus intersects the second surface.
 9. The method ofclaim 8, wherein the first segment, the second segment, and the thirdsegment are each marked with a graphical feature corresponding to theirrespective likelihood that the patient has peripheral arterial disease.10. The method of claim 8, wherein the first segment, the secondsegment, and the third segment are each marked with a textual featurecorresponding to their respective likelihood that the patient hasperipheral arterial disease.
 11. The method of claim 8, wherein arespective length of each of the first segment, the second segment, andthe third segment is based on statistical analysis of data associatedwith a plurality of patients.
 12. The method of claim 8, wherein thefirst surface further comprises a first indicator that represents a meanplus standard deviation of the patients that have peripheral arterialdisease.
 13. The method of claim 8, wherein the first segment and thesecond segment are separated by a first segment marker, and the secondsegment and the third segment are separated by a third segment marker.14. The method of claim 8, wherein the measuring apparatus furthercomprises a fourth segment in series with and adjacent to the firstsegment, wherein said wrapping comprises: holding, by a user, the fourthsegment that wraps measuring apparatus around the calf of the patient.